OPEN Statistical optimization of experimental parameters for extracellular synthesis of by a novel haloalaliphilic Alkalibacillus sp.W7 Hend M. H. Al‑Kordy1, Soraya A. Sabry2 & Mona E. M. Mabrouk1*

Green synthesis of zinc oxide nanoparticles (ZnO NPs) through simple, rapid, eco-friendly and an economical method with a new haloalkaliphilic bacterial strain (Alkalibacillus sp. W7) was investigated. Response surface methodology (RSM) based on Box-Behnken design (BP) was used

to optimize the process parameters ­(ZnSO4.7H2O concentration, temperature, and pH) afecting the size of Alkalibacillus-ZnO NPs (Alk-ZnO NPs). The synthesized nanoparticles were characterized using UV–visible spectrum, X-ray difraction (XRD), Scanning electron microscope-energy dispersive X-ray spectroscopy (SEM–EDX), Transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR) and Zeta potential. The UV–Vis spectrum of ZnO NPs revealed a characteristic surface plasmon resonance (SPR) peak at 310 nm. XRD pattern confrmed the hexagonal wurtzite structure of highly pure with a crystallite size 19.5 nm. TEM proved the quasi-spherical shape nanoparticles of size ranging from 1 to 30 nm. SEM–EDX showed spherical shaped and displayed a maximum elemental distribution of zinc and . FTIR provided an evidence that the biofunctional groups of metabolites in Alkalibacillus sp.W7 supernatant acted as viable reducing, capping and stabilizing agents.

Nanoparticles (NPs) with at least one dimension sized from 1 to 100 nm­ 1exhibit unique features owing to their extremely small size and high surface area to volume ratio, which have attributed to the signifcant diferences in the properties over their bulk counterparts­ 1,2. Te increasing research in the feld of nanotechnology has infuenced many areas such as energy, medicine, electronics, environment, catalysts and space industries­ 3–5. Te synthesis of nanoparticles with the help of microorganisms has no harmful impacts, does not require use of hazardous chemicals, energy efcient, simple, clean, economical, and provides greater biocompatibility espe- cially in the clinical and biomedical applications­ 6. In addition the various natural materials in microorganisms function as a potential biofactory for the reduction and stabilization of the nanoparticles­ 7,8. Moreover, simple downstream processing provides greater biocompatibility in the uses of nanoparticles for pharmaceutical and biomedical applications and efective sources for high productivity and purity­ 9,10. One of the few disadvantages for microbial synthesis of nanoparticles is the tedious purifcation steps and poor understanding of the mecha- nisms controlling the shape, size, and mono dispersity.Also, scaling up the production processing for industrial applications is a challenge for its commercialization. Another challenge is slection of biocatalyst and optimization of reaction condition to achieve better yield and small size­ 9,10. Zinc oxide nanoparticles (ZnO NPs) are one of the most important metal oxide with many signifcant fea- tures such as chemical and physical stability, high catalytic activity, efective antibacterial activity as well as intensive (UV) and infrared (IR) ­ 11. Tey are used in an array of products and wide range of ­applications1,12,13. Traditionally, ZnO NPs synthesized by various physicochemical methods sufer from drawbacks such as high cost, requirement of elevated temperature, high pressure, specialized equipment, use of toxic and environmentally hazardous chemicals; resulting in high energy consumption and the generation of large amounts of waste which

1Botany and Microbiology Department, Faculty of Science, Damanhour University, Damanhour, Egypt. 2Botany and Microbiology Department, Faculty of Science, Alexandria University, Alexandria, Egypt. *email: mona_ [email protected]

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Figure 1. UV–vis absorption spectra of biosynthesised Alk-ZnO NPs, with maximum absorption at 334 nm. Inset shows visual observation of color change (I) Pure precursor (ZnSO­ 4.7H2O), (II) reducing agent (culture supernatant), (III) clusters of Alk-ZnO NPs formed afer mixing reducing agent and precursor.

pose environmental ­risks1. Microbes such as bacteria, fungi, and yeast play an important role in the biological synthesis of metal and metal oxide NPs. Nevertheless, the biological synthesis of ZnO NPs using microbes still remains ­unexplored1. Te formation of nanomaterials by extremophiles is a promising approach for the biosynthesis of metallic nanoparticles. Extremophiles are important in the synthesis of NPs because they allow for the adjustment of the environment to fne-tune size, shape, stability, and capping proteins. Tis in turn optimizes the NPs for the large number of applications that they may ­fulfll14. From the literature survey, bacteria isolated from a challenged environment like salt alkaline habitats have never been explored as potential biofactories for the synthesis and stabilization of ZnO NPs. In an early report, Halomonas elongata IBRC-M 10214 has been recognized as a bio- factory, capable of producing ZnO NPs­ 15, whereas there was no literature available on nanoparticles synthesis by genus Alkalibacillus. Synthesis methods that control the size and shape of nanoparticles are useful in boosting their chemico- physical properties. It is imperative to optimize the parameters employed in the synthesis protocol to achieve good monodispersity, greater particle stability and excellent ­biocompatibility16,17. Te strong relationship between size and properties of nanoparticles has provided numerous chances for many scientifc areas­ 18. Optimization of factors such as temperature, pH value, precursor concentration, mixture ratio, and reaction time, and their interaction afect the biological synthesis of metal nanoparticles­ 19 have been very poorly evalu- ated for ZnO ­nanoparticles20. Statistical experiment strategy such as response surface methodology (RSM) is used to determine the relationship between the response variable (e.g., NPs size) and the factors afecting their size. Further, it determines the accurate optimum value (s) of the examined variables that give (s) a maximum or minimum optimal response, depending on the product or on the process in ­question16. Tis method consists of a number of mathematical and statistical techniques which improves and optimizes processes through evaluating the relationship between the independent variables and responses­ 21. Tis method was successfully applied in many areas of biotechnology, including some recent studies for green synthesis of ­nanoparticles16,17,22,23. Terefore, this innovative study explores an efcient, single step, green, environment-friendly and low-cost method for extracellular biosynthesis of ZnO nanoparticles using Alkalibacillus sp.W7 as a reducing as well as surface stabilizing agent. Te reaction parameters including temperature, concentration of Zinc sulphate, and pH value that afect the average diameter size of ZnO nanoparticles were statistically optimized with the Box–Behnken experimental design method. Te biosynthesized ZnO NPs were characterized and confrmed through various techniques such as UV–visible spectroscopy followed by SEM, EDX, TEM, XRD, and FTIR. Results and discussion Extracellular synthesis of Alk‑ZnO NPs. To the best of our knowledge, this is the frst report employing Alkalibacillus sp. W7 as a natural nanofactory for extracellular synthesis of ZnO NPs. Te preliminary detection of nanoparticles formation was distinguished through visual observation of cloudy white clusters deposited at the bottom of the tube compared to control (Fig. 1). Te cloudy white precipitate arised as a result of reduction of Zn­ +2 to elemental ­Zn0 by active metabolites in the culture fltrate and is due to the excitation of surface plasmon resonance (SPR) of the ZnO nanoparticles­ 24. It has been demonstrated that the proteins, enzymes as well as other active metabolites secreted by microorganisms are the principal biomolecules involved in the formation of metal/metal oxide nanoparticles­ 4,25. It was found that the UV–vis absorption spectrum of biosyn-

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Variable coded and actual values

Trial X1 pH X2 Temperature (°C) X3 ­ZnSO4.7H2O (mM)) Average size (nm) of ZnO NPs 1 1(9) 0 (30) 1(10) 24.03 2 0 (8) 0 (30) 0 (8) 21.4 3 1(9) 0 (30) − 1(2) 36.46 4 0 (8) 0 (30) 0 (8) 20.5 5 1(9) 1(50) 0 (8) 27.6 6 − 1(7) 1(50) 0 (8) 32.7 7 − 1(7) 0 (30) 1(10) 26.4 8 0 (8) 1(50) 1(10) 27.14 9 0 (8) 1(50) − 1(2) 33.6 10 − 1(7) 0 (30) − 1(2) 28.02 11 − 1(7) − 1(20) 0 (8) 29.4 12 0 (8) 0 (30) 0 (8) 20.7 13 0 (8) − 1(20) 1(10) 26.02 14 1(9) − 1(20) 0 (8) 25.5 15 0 (8) − 1(20) − 1(2) 31.5

Table 1. Design matrix of Box–Behnken experiments showing coded and actual values of the evaluated independent variables along with response.

Level of Source of Degree of Fishers’s function signifcance Determination variations freedom Sum of squares Mean square F-value (P-value) coefcient ­R2 Regression 9 305.371 33.93 15.533 0.003783 0.96546 Residual 5 10.922 2.184 Total 14 316.293

Table 2. Analysis of variance (ANOVA) of the ftted quadratic polynomial model.

thesized Alk-ZnO NPs demonstrated SPRcharacteristic maximum absorption peak at 334 nm (Fig. 1), several biofabricated ZnO NPs revealed comparable absorption ­peaks20,24,26. No other peaks were observed in the spec- trum, indicating high purity and crystallinity of Alk-ZnO NPs. Te absorption peak depends on size and shape of synthesized NPs.

Optimization parameters of Alk‑ZnO NPs size through Box Behnken design. Te average diam- eter of metal nanoparticles can be afected by some factors including pH, salt concentration and temperature of ­incubation21. Response surface methodology was applied to investigate the relation between the factors (pH, temperature and ­ZnSO4.7H2O concentration) on the average size of Alk-ZnO NPs. For each trial, the average particle size acquired from the regression equation for the 15 combinations are illustrated in Table 1. It was observed that the smallest sized particles were produced from trials 2, 4, and 12. Te determination coefcient ­(R2) values provide a measure of how much variability in the observed response can be explained by the experimental factors and their interactions. Te closer the R­ 2 value to 1, the stronger the model is, the bet- ter it predicts the response and has a very high correlation­ 22,27. Te determination coefcient (R­ 2) of the model (0.9654) indicates 96.54% of variability in the response. Terefore, the present R­ 2-value indicates a very good ft between the observed and predicted responses and implies that the model is reliable in the present study. Analysis of variance (ANOVA) was used to evaluate the signifcance and adequacy of the regression model. According to ANOVA results (Table 2), the model was highly appropriate; the relationship between the independ- ent variables and the average size of nanoparticles was evident from low P-value (0.00378). Te value of adjusted-R2 (0.9033) was also very high indicating a high signifcance of the model­ 22 and sug- gested that the total variation of 90.33% average diameter size of nanoparticles is attributed to the independent variables and only about 9.67% of the total variation cannot be explained by the model. All values of model coefcients were calculated by multiple regression analysis. Te signifcance of each coefcient was determined by the Student’s t-test and P-value, as illustrated in Table 3. Based on the analysis of regression coefcients of the quadratic model, among the three tested variables, the linear efects of reaction pH ­(X1), and reaction temperature ­(X2) exhibited a negative relationship on particle size, while zinc sulphate concentration ­(X3) exhibited a positive relationship. P-value indicates the signifcance of each of the coefcients which is important to understand the pattern of the mutual interaction among variables. Te smaller the magnitude of the P, the more signifcant is the corre- sponding coefcient. According to the degree of signifcance (P ≤ 0.01, signifcant at 99% level), the linear term of pH ­(X1) had the most dramatic negative signifcant efect on NPs size among all linear efects. In contrast, the

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Variables Coefcients Main efect t Stat P value Confdence level (%) Intercept 230.9812 461.962 4.441171 0.00000 100

X1 (pH) − 50.2081 − 100.416 − 4.0173 0.010148 99.10991

X2 (°C) − 1.00097 − 2.00194 − 2.06055 0.094367 91.39283

X3 ­(ZnSO4) 2.895308 5.790616 1.762809 0.138222 85.95297

X1X2 − 0.0418 − 0.08359 − 0.86907 0.424555 58.14298

X1X3 − 0.79829 − 1.59659 − 4.56962 0.006004 99.43325

X2X3 − 0.00029 − 0.00059 − 0.02589 0.980343 1.992987

X1X1 3.549259 7.098519 4.601892 0.00583 99.48717

X2X2 0.020132 0.040264 5.105393 0.003753 99.66835

X3X3 0.22403 0.448059 3.309396 0.021255 98.13707

Table 3. Regression analysis for optimizing ZnO nanoparticles size using Box–Behnken design.

Figure 2. A Pareto chart illustrating the main efects of Box-Behnken result, with the order of signifcance of the variables afecting Alk-ZnO NPs size. Bars that exceed the vertical line indicate the signifcance of the terms (P < 0.05).

2 2 2 quadratic terms for pH ­(X1 ), temperature ­(X2 ) and metal concentration ­(X3 ) had a signifcant positive efect; meaning that they could be considered as limiting factors and little variation in their values will alter the size of nanoparticles. In addition, only interaction between pH (X­ 1) and metal concentration (X­ 3) was noted to have a negative signifcant efect. Te Pareto chart identifed as a useful tool for determining the most signifcant efects­ 28 was used to illustrate the order of signifcance of the diferent factors on Alk-ZnO NPs size. Each bar length on a standardized Pareto chart (Fig. 2) is proportional to the absolute value of its related estimated efect or regression coefcient. Design Expert sofware was used to ft a second order polynomial model to the experimental results to predict the size of NPs within the experimental constraints. Te following second order polynomial equation represents the empirical relationship between NP size and the three independent variables:

Y(NPsSize) = 230.9812 − 50.2081X1 − 1.00097X2 + 2.895308X3 − 0.0418X1X2 − 0.79829X1X3 2 2 2 − 0.00029X2X3 + 3.549259X1 + 0.020132X2 + 0.22403X3

Te coefcients sign determines the response performance. Here, coefcient with positive efect means decrease in particle size, while a negative efect means increase in particle size. In addition, at higher absolute value of a coefcient, the efect of variable is higher. Terefore, according to the previous equation, pH of the reaction is the variable with the strongest infuence on NPs size.

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Figure 3. Tree-dimensional response surface graphs and contour plots showing the efect of independent variables on the average size of Alk-ZnO NPs; (A) Efect of metal concentation and temperature, (B) Efect of metal concentation and pH and (C) Efect of temperature and pH.

From polynomial models, response surface curves were plotted using Design-Expert 7.0, a trial version sofware to determine the efects of factors and their combinations that optimize the response. Tese three- dimensional plots and their respective contour plots provided a visual interpretation of the interaction of two test variables with the third one held at a constant level and facilitated the location of optimum values of the variables for synthesis of the smallest NPs. Signifcance of the interaction plots between the corresponding variables was indicated by an elliptical or circular or saddle nature of the contour plots­ 23. Te contour plots (Fig. 3) reveal that the optimal point for decreasing the average diameter of Alk-ZnO NPs was located inside the experimental region, which confrms the adequacy of the independent variable concentration ranges used in this study. Te response surfaces obtained were concave, indicating that the operating conditions were well-defned and optimum. Figure 3A represents the interaction between temperature and metal concentration and reveals that the average diameter size decreased with gradual increasing in both metal concentration and temperature. Tis might be explained that increasing metal concentration to a certain point allows particle growth at a faster rate and generates NPs with smaller size. Moreover, higher metal precursor concentration in the reac- tion mixture may increase the aggregation of the growing NPs, which resulted in the formation of larger NPs 21,29 30 size­ . Phanjom &Ahmed reported that ­AgNO3 concentration up to 8 mM, resulted in the formation of a smaller size, while the size increased at 9 and 10 mM concentrations. Tis efect was attributed to the lack of functional groups available for the reaction when the metal precursor concentration was increased. To achieve the smallest particle size, the middle levels of both metal concentration and temperature were used. Higher temperature resulted in the gradual increase in the NPs size. Unsuitable temperatures to increased nanoparticle size and loss of stability, as a result of denaturation, inactivation or low activity of the reductive enzymes and other active molecules involved in the biogenesis process­ 31,32. Additionally, it was suggested that the increase in temperature decreases NPs size which is normally due to increment in reaction rate and kinetic energy at higher ­temperatures29,33. Generally, the efect of temperature on the size and stability of the synthesized nanoparticles varies according to the microorganism ­used9. Figure 3B represents the mutual interaction of pH and metal concentration on Alk-ZnO NPs biosynthesis when temperature was fxed at optimum value. Te average diameter size decreased gradually with the increment of pH but at higher pH values, the size slightly increased. Tis may be due to the inactivation of biomolecules involved in the synthesis of Alk-ZnO NPs at low and high pHs­ 21. Generally, pH plays a signifcant role in nanoparticles synthesis, mainly because it has the ability to alter the shape of biomolecules that is responsible in capping and stabilizing the NPs­ 34. Also, plays a

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Figure 4. Scanning electron micrograph of Alk-ZnO NPs synthesized under optimum conditions at 35,000 × magnifcation.

substantial role in the and reducing power of enzymes and secondary metabolites present in cell-free extract­ 35. Zhang et al.36 stated that pH of the medium solution infuences the size and the texture of the synthesized nanoparticles. Modifcation in pH to alteration in the overall charge of bioactive molecules, which in turn facilitates their binding afnity and hence biomineralization of metal ions into ­nanoparticles37. Te obtained data reveal that alkaline pH and a high metal concentration are conditions that will generate smallest size of Alk-ZnO NPs. While, a higher or lower pH generated the larger size, which indicated that the catalytic activity of enzymes responsible for ­Zn2+ ions reduction appeared to be deactivated, thus causing an increase in the size of NPs. Figure 3C shows the combined efect of pH and temperature when metal concentration value was fxed at optimum value. It showed that higher values of pH and temperature supported the increase of Alk- ZnO NPs size. Te smallest size was obtained in the middle levels of both pH and temperature. Te synthesis of small sized ZnO NPs could be attributed to the increase in nucleation process rate as a result of a large number of OH ions. Te fnding is in agreement with that reported by Mata et al.38 who indicated that higher pH favored higher reducing power. Possible reason is that during the elevated pH, the reaction rate will be increased with subsequent crystallization into smaller particles, which involved the nucleation and growth processes of smaller particles from metal nuclei­ 39. Te study of physicochemical parameters of the reaction such metal ions concentrations, pH and temperature on Alk-ZnO NPs formation represents the efect of the direct connection between these factors on the particles size. By solving the model regression equation using the SOLVER function of MICROSOFT EXCEL tools, the smallest size Alk-ZnO NPs and the optimum values of these variables can be acquired. Te optimal values of the variables were temperature 33 °C, metal concentration 8 mM and pH 8. Te model predicts the smallest NPs size that can be obtained using the above optimum conditions to be 20.4 nm.

Verifcation of the model. In order to validate the obtained data and to evaluate the accuracy of the applied Box-Behnken statistical design, a verifcation experiment with optimum concentration of examined variables was carried out in three replicate and compared with the predicted data. Te results obtained demon- strated that the average size of nanoparticles was 17.5 nm, while the predicted value from the polynomial model was 20.4 nm. Tere was a little diference between the experimental and the predicted data. Te verifcation revealed a high degree of accuracy of the model, indicating the model validation under the tested conditions. Te measured particle size was less than the predicted by 14.22%. Verifcation experiment indicated validity, and reliability of response model and applicability of RSM to minimize the size of Alk-ZnO NPs. Additionally, in the present study, Al. sp.W7 could synthesize 0.493 g of NPs /L of bacterial supernatant in 24 h.

Characterization of Alk‑ZnO NPs. UV–visible spectroscopy. Alk-ZnO NPs synthesized under optimal conditions exhibited the surface plasmon resonance band shifed to a lower wavelength 310 nm, due to their large excitation binding energy­ 40. It is known from absorption spectroscopy that as particle size decreases, the energy increases. Tere is also an opposite ratio between band gap and the absorption ­wavelength41. Te corresponding band gap was found to be 4.00 eV. Our data are in good agreement with the earlier reports on biosynthesis of ZnO NPs­ 25,42. Aggregation is a common problem with nanoparticles which greatly decreases the surface area and, as a result, afects their physicochemical and biological ­properties43. It is worth to mention that the nanoparticles examined afer 10 months using UV–vis spectroscopy showed a peak at 310 nm, indicating their stability (Supplementary Figure S1).

Scanning electron microscopy analysis. Scanning electron microscopy provided further insight into the mor- phology and size of the synthesized ZnO NPs. Te micrograph illustrated in Fig. 4 proved that they had nano- sized range, smooth, irregular to nearly spherical with a uniform distribution with an average size ranging from 5 to 45 nm.

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Figure 5. Energy dispersive x-ray spectroscopic analysis of Alk-ZnO NPs. Other elemental signal as was also recorded possibly from enzymes or proteins present in the culture supernatant. Inset image of scanned area and elemental composition.

Energy‑dispersive X‑ray spectrum. Te Alk-ZnO NPs were subjected to an EDX spectrum to quantify the mix- ture of metal and present in the sample. Figure 5 clearly illustrates that the EDX spectrum of the fabri- cated NPs was recorded in the spot-profle mode from one of the densely populated nanoparticles area. Distinct peaks obtained for zinc and oxygen atoms represent the formation of ZnO NPs. Te elemental profle showed strong higher peak at 1 keV, characteristic to Zn and confrmed the formation of ZnO ­NPs44,45. Te weak signal of C atoms was also recorded and likely due to X-ray emission from carbohydrates/proteins/enzymes present in the bacterial cell free fltrate indicating their involvement in reduction and capping of the synthesized ZnO NPs. Te atomic percentages of the elements inset of Fig. 5 reveal zinc as the major element comprising more than 66.33% of total constituent along with oxygen 25.48%, which clearly also confrms the high purity of mediated zinc oxide nanoparticles. Additionally, the optical absorption signals of zinc were observed due to surface plas- mon resonance of ZnO ­NPs34,45, which is in agreement with previous reports­ 46,47. Te impurity free nanoparti- cles are promising in diferent application felds as antitumor, anti-microbial and antibioflm. Our results are in agreement with the results obtained by microbially synthesized ZnO ­NPs20,47,48, where pure form of nanoparticle was clearly depicted through EDX imaging.

Transmission electron microscopy. Transmission electron microscopic analysis provided exact morphology and size of Alk-ZnO NPs acquired from optimized synthesis conditions and revealed predominantly irregular to nearly hexagonal and quasi-spherical with legitimately agglomeration (Fig. 6A,B). Tis is a typical phenomenon of interaction of moisture and ZnO and inter-particle interactions (Van der Waals, electrostatic and magnetic forces)49,50. Te size distribution patterns reveal that the synthesized NPs ranged from 1–30 nm with an average size of 17 ± 1 nm (Fig. 6C). Tis result is in accordance with crystallite size calculated from the X-ray difraction. Similar hexagonal—quasi-spherical zinc oxide nanoparticles have been observed in Rhodococcus pyridinivorans ­NT246 and Lactobacillus plantarum ­VITES0751. It was previously reported that the smaller the size of ZnO NPs, the greater efcacy in inhibiting the growth of ­bacteria52.

X‑ray difraction analysis. X-ray difraction is taken in order to further confrm ZnO phase of the nano- particles. Te XRD pattern of the Alk-ZnO NPs fabricated under optimum conditions provided by the RSM having 2θ values with strong difractions peaks appear at 31.16°(100), 33.83°(002), 35.65°(101), 46.98°(102), 56.05°(110), 62.344°(103), 65.71°(200), 67.46°(112), 68.27°(201), 72.52°(004) and 76.84°(202) (Fig. 7). Te XRD difraction peaks were in good agreement with the reported literature and matched well with wurtzite ZnO of the Joint Committee on Powder Difraction Standards (JCPDS) Card number 36–1451. Tus XRD pattern shows ZnO NPs with a fne hexagonal crystalline structure formed with signifcant agreement with this reference fle, and no characteristic difraction peaks were observed other than ZnO, indicating that the bio-assisted NPs were free from other phase impurities and signifcantly had a high phase purity­ 13,53, which was confrmed by EDX analysis results. In addition, the strong and narrow difraction peaks indicated that the ZnO nanoparticles were of well crystalline structure­ 46. Our results are in good agreement with various XRD difractogram data reported for biologically synthesized ZnO nanoparticles­ 24,46. Te average crystalline size of NPs corresponding to the most intense difraction peak at 2θ = 35.65o (101) as calculated by Debye–Scherrer′s equation was found to be 19.5 nm. XRD results confrmed that Alk-ZnO NPs are highly crystalline, having hexagonal wurtzite crystalline structure which are compatible with other researchers’ work­ 20,55. XRD results also refect that the crystallization of the bio-organic phase occurs on the surface of the ZnO NPs. Te biosynthesized ZnO nanoparticles shared accord with the crystallite size calculated from TEM.

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Figure 6. Transmission electron microscopic image of Alk-ZnO NPs (A) low magnifcation (X80k), (B) high magnifcation (X120k), and (C) particle size distribution histogram.

Figure 7. X-ray difraction pattern of ZnO nanoparticles synthesized by Al. sp. W7 supernatant. All peaks indicate purity and crystalline nature. No traces of other impurity phases were detected.

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Figure 8. Zeta potential of Alk-ZnO NPs dispersed in .

Figure 9. Fourier transforms infrared spectroscopy (FTIR) of Alk-ZnO NPs.

Zeta potential. Zeta potential of the suspension is one of the key parameters in assessing the stability of the synthesized nanoparticle as it gives the net electrostatic potential of any particle in suspension. Te biosynthe- sized zinc oxide nanoparticles possessed a high positive potential value of 27.5 mv (Fig. 8) which indicates that they were highly stable and prevented agglomeration due to strong electrostatic repulsive forces between them. Nanoparticles with high negative or positive Zeta potential never aggregate due to electrostatic force of repulsion while particles with low zeta potential tend to focculate­ 51. It is generally considered that the zeta potential values (+ 30 mV to − 30 mV) result in good nanoparticle ­stability17,51, this result is comparable with zeta potential of zinc nanoparticles synthesized by Pseudomonas hibiscicola (24.64 mV)24. Positively charged nanoparticles show better attachment towards negatively charged cell membrane surface due to electrostatic attraction which leads to the penetration of ZnO NPs into the cells and thus enhanced toxicity towards microorganism­ 56.

Fourier transform infrared. FTIR spectrum was performed to determine the surface chemistry of the ZnO NPs and is used to access the details of functional groups involved in the biomolecules responsible for reducing and capping the bio-reduced ZnO ­NPs25,57. Te FTIR spectra for ZnO NPs are presented in Fig. 9. Te broad stretching vibrational band with high intensity observed at 3369 cm­ –1 is characteristic for hydroxyl (OH) or can correspond to the protein N‒H amide ­I51. It is well known that protein-nanoparticle interactions can occur either through free amine groups or cysteine residues in proteins and via the electrostatic attraction of negatively charged carboxylate groups in enzymes­ 53. Te absorption peak at 2922 cm­ −1 is attributed to C-H stretch of the methylene groups of the protein ­stretching21. Bands at 2352 and 2109 ­cm−1 are associated with the presence of primary amines and compounds­ 44. Tese peaks indicate the presence of proteins and other organic residues, which might have produced extracellularly by Al.sp. W7. Moreover, the absorption peak at

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1633 ­cm−1 corresponds to the stretching vibration of N–H bond of primary amines, alkyl C=C aromatic stretch- ing and open chain amino group in ­proteins26. Te absorption bands around 1630 ­cm−1 and 1384 ­cm−1 are due to asymmetric and symmetric of stretching carboxylate attached to the ZnO nanoparticles during ­synthesis58. Te absorption peaks at 1470 and 1380 ­cm−1 represent the carboxylate group ­(COO−)59. According to Tiwari et al.60, metal oxides exhibit absorption bands well below 1200 ­cm−1 arising due to interatomic vibrations. Generally metal oxides give absorption peaks in the regions between 500 and 900 cm­ −154. Strong peaks observed at 578.95 ­cm−1 and 906 ­cm−1 prominently indicate Zn–O bond. Tese fndings are in accordance with literature ­values20,41. Te stretching mode peaks are indicative of the successful synthesis of ZnO nanoparticles from Al.sp. W7 and FTIR spectral analysis reveals the subtle variations in biological components of culture supernatant associated with ZnO NPs formed. Te functional groups present in secreted proteins, enzymes and secondary metabolites in strain W7 culture supernatant are responsible for reduction of metal ions and biosynthesis of metallic nano- − particles. Te signifcant reduction capabilities of the biofunctional groups (R-OH, R-NH2, R-COO ) would reduce ­Zn2+ as electron acceptor to ­Zn0 resulting in the formation of ZnO NPs. Tese metabolites not only act as reducing agents but also act as capping agents providing stabilization against aggregation. Tese results are in agreement with previous report in green ZnO NPs ­synthesis13,61. Alkalibacillus sp. W7 nanoparticles showed good antibacterial activity, inhibiting the growth of Gram-negative and Gram-positive bacteria and also efcient photocatalytic degradation of the methylene blue and methyl orange dye under solar irradiation­ 62. Moreover, bioflm inhibition activity, anticancer and antioxidant potentials of the synthesized nanoparticles were also investigated. Materials and methods Microorganism and cultural conditions. Alkalibacillus sp. W7 an aerobic Gram-positive, rod-shaped bacterium, isolated from hypersaline Lake Al- Hamra in Wadi An-Natrun, Egypt was used in this study. Te 16S rDNA sequence was submitted to NCBI GenBank with an assigned accession number LC164829­ 63. Te strain was maintained on modifed Horikoshi-I ­medium64, containing (g/L): glucose,10; yeast extract,5; peptone,5; ­K2HPO4,1; ­MgSO4.7H2O,0.2; NaCl, 50; agar, 20; pH 8 and afer an incubation period of 48 h at 35 °C was kept at 4 °C and subcultured every month.

Synthesis of Alk‑ZnO NPs. Seed culture was prepared frstly by cultivation of Alkalibacillus sp. W7 aerobi- cally in 250 ml Erlenmeyer fask containing 50 mL of modifed Horikoshi-1 medium and incubated in a rotatory shaker (130 rpm) at 35 °C for 48 h (OD­ 600 = 1.0 ± 0.2). Sterile 50 ml of modifed Horikoshi-1 medium in 250 ml Erlenmeyer were inoculated with 2 ml of the fresh inoculum and incubated aerobically on a rotatory shaker incubator for 48 h at 35 °C and 130 rpm. Te cell free supernatant (CFS) collected by centrifugation at 5000 rpm for 15 min, then fltered with a 0.22 μm membrane flter (Millipore, USA) was used as a reducing agent for synthesis of Alk-ZnO NPs. Aqueous metal solution of 1 mM ZnSO­ 4.7H2O in distilled water was used as a precursor. Ten ml of zinc sulphate solution were mixed with 5 ml of Alkalibacillus sp. W7 cell free supernatant (2:1, V/V), and incubated for 48 h in dark under static condition at 35 °C to complete the ZnO NPs formation. Te color change was observed in the reaction mixture due to the reduction reaction. Simultaneously, control of sterile uninoculated media mixed with precursor salt solution was also maintained at same condition along with the experimental tubes in triplicate.

Statistical optimization of ZnO nanoparticles biosynthesis. Response surface methodology (RSM) is a collection of mathematical and statistical techniques which has been known as a tool for modeling within minimum number of experimental runs, determining the efects of important parameters and to identify their prominent interactions for the best ­response21,23. Response surface methodology based on Box-Behnken design­ 27 was used to evaluate the relationship between the factors that optimize the response. Te combined efect of three active independent variables; pH ­(X1), reac- tion temperature ­(X2) and Zinc sulphate concentration ­(X3) was considered for evaluation. Teir efects were evaluated with respect to responce (NPs size). Te levels of each individual variable were selected based on the results of preliminary experiments, involving optimization using the one-factor-at-a-time method. Table 1 shows the experimental Box-Behnken design matrix in the coded and actual levels of selected independent variables developed by Design Expert sofware (Version 7, Stat-Ease, Inc., USA) and the responce.

Statistical analysis. Hence, for a three-variable design, a total of 15 experimental runs were performed and their observations were ftted in the second order polynomial model, which is a mathematical expression used to determine the linear, quadratic, and cross efects of the tested independent variables to fnd the result and approximate the real answer as follows: 2 2 2 Y = β0 + β1x1 + β2x2 + β3x3 + β12x1x2 + β13x1x3 + β23x2x3 + β11x1 + β22x2 + β33x3

where Y is the dependent variable (size of NPs), X­ 1, ­X2, and X­ 3 are the independent variables, β0 is the regres- sion coefcient at center point, β1, β2, and β3 are the linear coefcient; β12, β13, and β23 are the second order interaction coefcients, and β11, β22, and β33 are the quadratic coefcients.

Purifcation of Alk‑ZnO NPs. Te nanoparticles were separated from the reaction mixture by high-speed centrifugation at 15,000 rpm for 10 min, then dispersed in sterilized distilled water and centrifuged again. Tis action was carried out for three times to remove the unreacted metals and the residual biological molecule impu- rities or any residual metabolites from native nanoparticle samples to obtain purifed ­NPs6. Finally, the obtained

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white color powder was washed with ethanol to remove ionic impurities, then dried overnight in an oven at 40 °C and characterized using diferent techniques.

Characterization of biogenic ZnO NPs. UV–visible spectroscopy. Te biosynthesized ZnO NPs were characterized using UV–Vis spectrophotometer (Termo Scientifc Evolution TM 300) in the wavelength region between 200-nm and 900-nm operated at a resolution of 1 nm and maximum absorbance was determined­ 65.

X‑ray difraction. X-ray difraction was performed using Phaser XRD-D2 powder X-ray difractometer (Bruker, Germany) supplied with Cu-Kα radiation over a wide range of the Bragg angles θ (10° ≤ 2θ ≤ 80°) oper- ated at 30 kV, 10 mA. Data was compared with known standard data published by the Joint Committee on Powder Difraction Standards (JCPDS Card No. 36–1451). Te mean of the crystallite size (nm) was determined from the XRD line broadening measurement using Debye Scherrerr’s equation: D = 0.89 /(βCosθ)

where λ is the wavelength of X-ray radiation, λ = 1.5406 Å, β is the full width at the half maximum (FWHM) of the most intense difraction peak, and θ is the difraction angle.

Scanning electron microscopy. Te shape and size of the ZnO NPs were determined using SEM JEOL IT 200, (JOEL Corp, Tokyo, Japan). Te biosynthesized powder was mixed into doubled distilled water and sonicated for 30 min. A small drop of this sample was allowed to dry on a slide to make a thin layer of NPs.

Energy‑dispersive X‑ray analysis. Te structure of Alk-ZnO NPs was characterized by energy-dispersive analy- sis X-ray (EDX) spectrum using X-ray micro-analyzer (Module Oxford 6587INCA X-sight) coupled with SEM– IT 200 scanning electron microscope (JOEL Corp, Tokyo, Japan) operated at 20 kV of an accelerating voltage for compositional analysis as well as conformation for the presence of elemental zinc.

Transmission electron microscopy. Te size and shape of Alk-ZnO NPs were observed using a transmission electron microscope TEM JEM-1400 plus, (JOEL Corp, Tokyo, Japan) operated at an accelerating voltage of 50 kV. A drop of ZnO NPs solution was placed on a carbon coated grid followed by water evaporation. Te average particles size and the size distribution histogram were determined from microscopic images using a particle size analyzer programe, Image J processing and analysis sofware (http://​imagej.​nih.​gov/​ij/​index.​html).

Zeta potential measurement. Te zeta potential was performed by dispersing 1 mg of ZnO NPs in 10 ml of distilled water followed by sonication for 5 min then measurement using Malvern Zetasizer Nano ZS analyzer (Malvern Instruments, Malvern, UK)66.

Fourier transforms infrared spectroscopy. FTIR analysis was done for identifcation of presumable biomolecules responsible for the reduction of the Zn­ +2 ions and formation and stability of ZnO NPs. Sample was prepared by mixing Alk-ZnO NPs with bromide KBr using hydraulic press and then dried to remove the moisture content. Infrared spectra were recorded over a range of 450–4000 ­cm–1 with FTIR spectrophotometer (FTIR spectrum Version 10.5.3, Perkin Elmer). Conclusions Te present study, built up the frst ever account of use of culture supernatant of Alkalibacillus sp. W7 towards extracellular synthesis of zinc oxide nanoparticles. Te response surface methodology was applied to optimize the conditions infuencing the Alk-ZnO NPs size. Te results revealed that the optimization of the reaction parameters was essentially needed and directly afected ZnO NPs size. Te ftness of the model was verifed and predicted values were confrmed. Te synthesized Alk-ZnO NPs with optimized conditions showed maximum absorption peak at 310 nm. Te XRD results confrmed the efciency of the synthesis process, evidencing the production of single crystalline NPs with hexagonal wurtzite structure. Te average size of synthesized NPs was 17.5 nm, exhibiting quasi-spherical with smooth surface which was confrmed by TEM and SEM analyses. EDX results confrmed the presence of zinc and oxygen with a pure phase. FTIR analysis clearly showed the formation of ZnO NPs and verifed the presence of various biomolecules secreted by Alkalibacillus sp. W7 acting as cap- ping and stabilizing agents. Tis green synthesis does not need any additive stabilizer which is a positive point in comparison with chemical methods. Our results confrm the potential of Alkalibacillus sp. W7 for ZnO NPs biosynthesis in a simple, fast, cost-efective, convenient and ecofriendly way. Furthermore, the results confrmed that the response surface methodology was benefcial for smaller ZnO NPs size synthesis with great stability over time, and the reaction parameters are directly afecting their size. Data availability All data produced during this study are included in this published article.

Received: 22 February 2021; Accepted: 11 May 2021

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Competing interests Te authors declare no competing interests.

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